PyExplainer: A Local Rule-Based Model-Agnostic Technique (Explainable AI)
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Updated
Jun 21, 2024 - Python
PyExplainer: A Local Rule-Based Model-Agnostic Technique (Explainable AI)
The implementation of Online Cross-Project JIT-SDP approaches proposed in the paper "Cross-Project Online Just-In-Time Software Defect Prediction" accepted in IEEE Transactions on Software Engineering (TSE), 2022, (accepted).
The defect data set of Solidity Smart Contracts
This repository contains the codes and temporary results used for the analyses for the paper: Liyan Song and Leandro Minku. "A Procedure to Continuously Evaluate Predictive Performance of Just-In-Time Software Defect Prediction Models During Software Development", IEEE Transactions on Software Engineering, 2022
Weka implementation of the cost-sensitive decision forest algorithm CSForest.
The project is designed in a componentized manner, and random forests are used in model development.
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